Martijn Lappenschaar

Anxiety and mood disorders in narcolepsy: a case–control study

INTRODUCTION Narcolepsy is a primary sleeping disorder with excessive daytime sleepiness and cataplexy as core symptoms. There is increasing interest in the psychiatric phenotype of narcolepsy. Although many authors suggest an overrepresentation of mood disorders, few systematic studies have been performed and conflicting results have been reported. Anxiety disorders in narcolepsy have only received little attention. METHODS We performed a case-control study in 60 narcolepsy patients and 120 age- and sex-matched controls from a previous population study. The Schedules for Clinical Assessment in Neuropsychiatry were used to assess symptoms and diagnostic classifications of mood and anxiety disorders. RESULTS Symptoms of mood disorders were reported by about one third of patients. However, the prevalence of formal mood disorder diagnoses - including major depression - was not increased. In contrast, more than half of the narcolepsy patients had anxiety or panic attacks. Thirty-five percent of the patients could be diagnosed with anxiety disorder (odds ratio=15.6), with social phobia being the most important diagnosis. There was no influence of age, sex, duration of illness or medication use on the prevalence of mood or anxiety symptoms and disorders. DISCUSSION Anxiety disorders, especially panic attacks and social phobias, often affect patients with narcolepsy. Although symptoms of mood disorders are present in many patients, the prevalence of major depression is not increased. Anxiety and mood symptoms could be secondary complications of the chronic symptoms of narcolepsy. Recent studies have shown that narcolepsy is caused by defective hypocretin signaling. As hypocretin neurotransmission is also involved in stress regulation and addiction, this raises the possibility that mood and anxiety symptoms are primary disease phenomena in narcolepsy.

Symptomatic overlap between attention-deficit/hyperactivity disorder and borderline personality disorder in women: the role of temperament and character traits.

OBJECTIVE There is substantial symptomatic overlap between attention-deficit/hyperactivity disorder (ADHD) and borderline personality disorder (BPD) in adults, but the nature of the relationship between these disorders needs further clarification. The role of temperament and character traits in the differentiation of classes of patients with similar ADHD and BPD symptom profiles was examined and possible pathways between early temperament and future ADHD and/or BPD were hypothesized. METHODS Structured diagnostic interviews were conducted in 103 female patients to assess current Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition symptoms of ADHD and BPD, and parent interviews were used to assess ADHD symptoms in childhood. Classes of subjects with homogeneous symptom profiles were identified using latent class analysis. Temperament and character traits were assessed using the Temperament and Character Inventory of Cloninger et al; scores were then compared across the latent classes. RESULTS Latent class analysis revealed 4 mutually exclusive classes of patients: 1 with only ADHD symptoms; 1 with BPD symptoms and ADHD symptoms of hyperactivity; 1 with BPD symptoms and ADHD symptoms of inattention, hyperactivity, and impulsivity; and 1 with BPD symptoms and ADHD symptoms of inattention and hyperactivity. High Novelty Seeking was found in all classes except for the class with symptoms of BPD and only the hyperactivity aspect of ADHD. The highest Novelty Seeking temperament scores were found in that class of patients with both symptoms of BPD and symptoms in all areas of ADHD. High Harm Avoidance, low Cooperativeness, and low Self-directedness were specifically related to classes containing BPD symptoms. CONCLUSIONS Classes of ADHD and BPD symptoms are associated with specific temperament and character configurations. Novelty Seeking was associated with the inattention symptoms of ADHD. An outspoken Novelty Seeking temperament suggests vulnerability for the development of ADHD and co-occurring BPD. Contrary to patients with combined ADHD and BPD symptoms, patients with only symptoms of ADHD showed normal character development and thus an absence of a personality disorder. Assessment of temperament and character traits can improve our understanding of the complex relationship between ADHD and BPD.

Lifespan attention deficit/hyperactivity disorder and borderline personality disorder symptoms in female patients: A latent class approach

Attention-deficit/hyperactivity disorder (ADHD) and borderline personality disorder (BPD) are frequently comorbid. To contribute to a better understanding of the associations regularly found between ADHD and BPD, on the one hand, and the developmental pathways for these disorders, on the other hand, latent class analyses (LCA) were undertaken to identify classes differing in profiles of childhood symptoms of ADHD and adult symptoms of ADHD and BPD. Diagnostic interviews with 103 female outpatients meeting the criteria for ADHD and/or BPD were used to assess current DSM-IV symptoms; childhood symptoms of ADHD were assessed in parent interviews. The latent classes were examined in relation to the DSM-IV conceptualizations of ADHD and BPD. And relations between childhood and adult classes were examined to hypothesize about developmental trajectories. LCA revealed an optimal solution with four distinct symptom profiles: only ADHD symptoms; BPD symptoms and only ADHD symptoms of hyperactivity; BPD symptoms and ADHD symptoms of inattention and hyperactivity; BPD symptoms and ADHD symptoms of inattention, hyperactivity and impulsivity. All patients with BPD had some ADHD symptoms in both adulthood and childhood. Hyperactivity was least discriminative of adult classes. Adult hyperactivity was not always preceded by childhood hyperactivity; some cases of comorbid ADHD and BPD symptoms were not preceded by significant childhood ADHD symptoms; and some cases of predominantly BPD symptoms could be traced back to combined symptoms of ADHD in childhood. The results underline the importance of taking ADHD diagnoses into account with BPD. ADHD classification subtypes may not be permanent over time, and different developmental pathways to adult ADHD and BPD should therefore be investigated.

Severe fatigue in narcolepsy with cataplexy.

Excessive daytime sleepiness (EDS) is the core symptom of narcolepsy. However, there have been indications that fatigue – which should be separated from EDS – is also a frequent complaint. We determined the prevalence of severe fatigue in a group of narcolepsy patients and its relation with excessive daytime sleepiness, psychological distress, functional impairment and quality of life. We included 80 patients fulfilling the International Classification of Sleep Disorders (ICSD)‐2 diagnostic criteria of narcolepsy with cataplexy. Fatigue was measured using the Checklist Individual Strength (CIS). In addition psychological distress, including symptoms of depression, functional impairment and quality of life, were assessed. Comparisons were made between patients with (CIS‐fatigue score ≥ 35) and without severe experienced fatigue. Fifty patients (62.5%) reported severe fatigue. There were no sex or age differences between patients with and without severe fatigue. Both fatigued and non‐fatigued patients had the same amount of daytime sleepiness (Epworth Sleepiness Score 14.3 ± 4.2 versus 13.1 ± 4.4, P = 0.22), confirming the separation between sleepiness and fatigue. Interestingly, fatigued patients more often used stimulant medication (64% versus 40%, P = 0.02). Severe fatigue was associated with a significantly increased functional impairment, increased depressive symptoms and a lowered general quality of life. In conclusion, a majority of patients with narcolepsy suffer from severe fatigue, which can be distinguished from daytime sleepiness, and results in severe functional impairment.

Multilevel Bayesian networks for the analysis of hierarchical health care data

OBJECTIVE Large health care datasets normally have a hierarchical structure, in terms of levels, as the data have been obtained from different practices, hospitals, or regions. Multilevel regression is the technique commonly used to deal with such multilevel data. However, for the statistical analysis of interactions between entities from a domain, multilevel regression yields little to no insight. While Bayesian networks have proved to be useful for analysis of interactions, they do not have the capability to deal with hierarchical data. In this paper, we describe a new formalism, which we call multilevel Bayesian networks; its effectiveness for the analysis of hierarchically structured health care data is studied from the perspective of multimorbidity. METHODS Multilevel Bayesian networks are formally defined and applied to analyze clinical data from family practices in The Netherlands with the aim to predict interactions between heart failure and diabetes mellitus. We compare the results obtained with multilevel regression. RESULTS The results obtained by multilevel Bayesian networks closely resembled those obtained by multilevel regression. For both diseases, the area under the curve of the prediction model improved, and the net reclassification improvements were significantly positive. In addition, the models offered considerable more insight, through its internal structure, into the interactions between the diseases. CONCLUSIONS Multilevel Bayesian networks offer a suitable alternative to multilevel regression when analyzing hierarchical health care data. They provide more insight into the interactions between multiple diseases. Moreover, a multilevel Bayesian network model can be used for the prediction of the occurrence of multiple diseases, even when some of the predictors are unknown, which is typically the case in medicine.

Multilevel temporal Bayesian networks can model longitudinal change in multimorbidity

OBJECTIVES Although the course of single diseases can be studied using traditional epidemiologic techniques, these methods cannot capture the complex joint evolutionary course of multiple disorders. In this study, multilevel temporal Bayesian networks were adopted to study the course of multimorbidity in the expectation that this would yield new clinical insight. STUDY DESIGN AND SETTING Clinical data of patients were extracted from 90 general practice registries in the Netherlands. One and half million patient-years were used for analysis. The simultaneous progression of six chronic cardiovascular conditions was investigated, correcting for both patient and practice-related variables. RESULTS Cumulative incidence rates of one or more new morbidities rapidly increase with the number of morbidities present at baseline, ranging up to 47% and 76% for 3- and 5-year follow-ups, respectively. Hypertension and lipid disorders, as health risk factors, increase the cumulative incidence rates of both individual and multiple disorders. Moreover, in their presence, the observed cumulative incidence rates of combinations of cardiovascular disorders, that is, multimorbidity differs significantly from the expected rates. CONCLUSION There are clear synergies between health risks and chronic diseases when multimorbidity within a patient progresses over time. The method used here supports a more comprehensive analysis of such synergies compared with what can be obtained by traditional statistics.

The Structure of Autism Spectrum Disorder Symptoms in the General Population at 18 Months

It is unclear whether symptoms of autism spectrum disorder (ASD) in young children in the population fit the three-factor structure of ASD as described in the DSM-IV, and cluster together in individual subjects. This study analysed questionnaire data on ASD symptoms filled in by mothers of 11,332 18-month-old children that was collected in the context of the Norwegian Mother and Child Cohort Study conducted by the Norwegian Institute of Public Health. Confirmatory Factor Analyses showed that the three-factor model had a significantly better fit then the two- and one-factor model of ASD symptoms. Latent class analysis revealed four homogeneous groups of children (classes) with different scores for Social Interaction and Communication at one hand and Stereotypies/Rigidity at the other hand.

One-year follow up of cardiac anxiety after a myocardial infarction: a latent class analysis.

INTRODUCTION Longitudinal elevated depressive symptom scores are associated with a less favorable cardiac outcome. Although anxiety has received less attention, meta-analysis suggests that high baseline levels of general anxiety might worsen cardiac outcome. The objective of this study was to explore the longitudinal course of cardiac anxiety after a myocardial infarction (MI). METHODS The Cardiac Anxiety Questionnaire (CAQ) was administered to 194 patients hospitalized for MI after admission, and one, three, six and twelve months after discharge. Latent class growth analysis (LCGA) was performed to identify groups based on cardiac anxiety course. Between group differences were checked on relevant socio-demographic, cardiac and psychiatric variables. RESULTS LCGA identified three groups with stable CAQ levels over time, indicative of high (7.7%), intermediate (45.4%) and low (30.4%) levels of cardiac anxiety, respectively. A fourth group (16.5%) reported high levels of cardiac anxiety that decreased over time. Between group differences were of particular interest for the two subgroups that started high in cardiac anxiety, since these may differentiate patients with spontaneous remission from those who might be in need of treatment. Patients in whom cardiac anxiety persisted were less often employed, had more diabetes mellitus, a history of acute coronary syndrome, depressive symptoms, anxiety and avoidance at baseline and a lower quality of life at follow-up. CONCLUSION This first study addressing cardiac anxiety after an MI identified four trajectories. Future studies should focus on cardiac outcome and treatment strategies for cardiac anxiety in the subgroup with persistent high anxiety levels.

Homogeneous Combinations of ASD-ADHD Traits and Their Cognitive and Behavioral Correlates in a Population-Based Sample.

Objective: Autism Spectrum Disorders (ASD) and ADHD are assumed to be the extreme manifestations of continuous heterogeneous traits that frequently co-occur. This study aims to identify subgroups of children with distinct ASD–ADHD trait profiles in the general population, using measures sensitive across both trait continua, and show how these subgroups differ in cognitive functioning. Method: We examined 378 children (6-13 years) from a population-based sample. Results: Latent class analyses (LCA) detected three concordant classes with low (10.1%), medium (54.2%), or high (13.2%) scores on both traits, and two discordant classes with more ADHD than ASD characteristics (ADHD > ASD, 18.3%) and vice versa (ASD > ADHD, 4.2%). Findings suggest that ASD and ADHD traits usually are strongly related in the unaffected population, and that a minority of children displays atypical discordant trait profiles characterized by differential visual-spatial functioning. Conclusion: This dissociation suggests that heterogeneity in ASD and ADHD is rooted in heterogeneity in the lower unaffected end of the distribution.

Do High and Low Extremes of ADHD and ASD Trait Continua Represent Maladaptive Behavioral and Cognitive Outcomes? A Population-Based Study

Objective: Attention deficit hyperactivity disorder (ADHD) and autism spectrum disorders (ASD) are thought to reflect the high, symptomatic extreme of quantitative trait continua. However, extreme deviations in either direction on disorder continua, high and low, may both represent maladaptive behavioral and cognitive outcomes. We aimed to test this hypothesis. Method: In a population sample of 378 children, ADHD and ASD traits were rated by parents on questionnaires that provide resolution at high and low extremes of the ADHD and ASD trait continua. ADHD and ASD traits were related to parent-ratings of internalizing and externalizing behavior problems and tests of cognitive functioning using polynomial regression. Results: The low ends of the ADHD and ASD trait continua were related to fewer behavior problems and better cognitive functioning than symptomatic ends. Conclusion: Studying the correlates of the low continuum ends may deepen our understanding of the mechanisms underlying adaptive behavioral and cognitive outcomes.